A new upscaling method for microscopic fluid flow based on digital rocks

This report presents our new findings in microscopic fluid flow based on digital rocks. Permeability of digital rocks can be estimated by pore-scale simulations using the Stokes equation, but the computational cost can be extremely high due to the complicated pore geometry and the large number of voxels. In this study, a novel method is proposed to simplify the three-dimensional pore-scale simulation to multiple decoupled two- dimensional ones, and each two-dimensional simulation provides the velocity distribution over a slice. By this decoupled simulation approach, the expensive simulation based on the Stokes equation is conducted only on two-dimensional domains, and the final three- dimensional simulation of Darcy equation using the finite difference method is very cheap. The proposed method is validated by both sandstone and carbonate rock samples and shows significant enhancement in the computational speed. This work sheds light on large-scale microscopic fluid flow based on digital rocks.Cited as: Liao, Q., Xue, L., Wang, B., Lei, G. A new upscaling method for microscopic fluid flow based on digital rocks. Advances in Geo-Energy Research, 2022, 6(4): 357-358. https://doi.org/10.46690/ager.2022.04.1

APyCE: A Python module for parsing and visualizing 3D reservoir digital twin models

Engineers, geoscientists, and analysts can benefit from fast, easy, and real-time immersive 3D visualization to enhance their understanding and collaboration in a virtual 3D world. However, converting 3D reservoir data formats between different software programs and open-source standards can be challenging due to the complexity of programming and discrepancies in internal data structures. This paper introduces an open-source Python implementation focused on parsing industry reservoir data formats into a popular opensource visualization data format, Visual Toolkit files. Using object-oriented programming, a simple workflow was developed to export corner-point grids to Visual Toolkit-hexahedron structures. To demonstrate the utility of the software, standard raw input files of reservoir models are processed and visualized using Paraview. This tool aims to accelerate the digital transformation of the oil and gas industry in terms of 3D digital content generation and collaboration.Document Type: Short communicationCited as: Tosta, M., Oliveira, G. P., Wang, B., Chen, Z., Liao, Q. APyCE: A Python module for parsing and visualizing 3D reservoir digital twin models. Advances in Geo-Energy Research, 2023, 8(3): 206-210. https://doi.org/10.46690/ager.2023.06.0

Stress dependent gas-water relative permeability in gas hydrates: A theoretical model

        Research activities are currently being conducted to study multiphase flow in hydrate-bearing sediments (HBS). In this study, in view of the assumption that hydrates are evenly distributed in HBS with two major hydrate-growth patterns, i.e., pore filling hydrates (PF hydrates), wall coating hydrates (WC hydrates) and a combination of the two, a theoretical relative  permeability model is proposed for gas-water flow through HBS. Besides, in this proposed model, the change in pore structure (e.g., pore radius) of HBS due to effective stress is taken into account. Then, model validation is performed by comparing the predicted results from the derived model with that from the existing model and test data. By setting the value of hydrate saturation to zero, our derived model can be reducible to the existing model, which demonstrates that the existing model is a special case of our model. The results reveal that, under the same saturation, relative permeability to water Krw (or gas Krg) in PF hydrates is smaller than that in WC hydrates. Moreover, the morphological characteristics of relative permeability curve (relative permeability versus gas saturation) for WC hydrate and PF hydrate are different.Cited as: Lei, G., Liao, Q., Chen, W., Lin, Q., Zhang, L., Xue, L. Stress dependent gas-water relative permeability in gas hydrates: A theoretical model. Advances in Geo-Energy Research, 2020, 4(3): 326-338, doi: 10.46690/ager.2020.03.1

Physically-based urban stormwater quality modelling: An efficient approach for calibration and sensitivity analysis

International audiencePhysically-based urban stormwater quality modelling is helpful for increasing the understanding of spatial-temporal dynamics of urban pollution, and for designing innovative management technologies. However, because of the high computational cost, calibration and validation of physically-based models is still challenging. In this context, this study aims to develop a new meta-model based framework for efficient calibration and sensitivity analysis of complex and computationally intensive physically-based models. The proposed approach is applied to the FullSWOF-HR model. According to the average rainfall intensity, 21 rainfall events are categorized into three groups, such as 9 light rains, 6 moderate rains and 6 heavy rains. After upscaling the original high-resolution model, 77 parameter nodes are selected by using the adaptive stochastic collocation method with sparse grids algorithm on the lower-resolution surrogate. 77 simulation runs are then performed with the original model for three representative rainfall events, respectively. The interpolating polynomials of the original models are hence generated. Once the meta-model is constructed, we performed the sensitivity analysis with the variance-based Sobol's method, the results of which are consistent with our previous studies. Calibration process of the meta-model is based on the Markov chain Monte Carlo method. The optimized parameters are verified with the original model and then validated for different rainfall events. These promising results show that the proposed meta-model based approach can efficiently perform sensitivity analysis and parameter optimization for complex physical stormwater quality models, and hence will be very helpful for spreading the detailed water quantity and quality modelling for urban water management issues

Efficient Calibration and Validation of Physical Stormwater Quality Modelling by Meta-model Based Approach

International audienceModel calibration and validation is still challenging for applications of physical stormwater quality model in the field of urban drainage modelling. In this context, this study aims to develop a new meta-model based framework for efficient calibration of complex and computationally intensive physically-based models. The proposed approach is applied to the physical FullSWOF-HR model for optimizing the washoff parameters. According to the average rainfall intensity, eight rainfall events are categorized into three groups for parameter optimisation, such as three light rains, three moderate rains and two heavy rains. After upscaling the original model, 77 parameter sampling experiments can be defined by a convergence analysis. Applying these 77 parameters series in FullSWOF-HR simulation runs, the interpolating polynomial of the original model is then generated by using the adaptive stochastic collocation method, which adopts sparse grid algorithm and selects the important parameters adaptively and automatically. Calibration process of the meta-model is based on the Markov chain Monte Carlo (MCMC) method. The optimized parameters are verified with the original model and then validated for different rainfall events. These promising results show that the proposed meta-model based approach can efficiently calibrate parameters for complex physical stormwater quality models. Our ongoing work focuses on the sensitivity/uncertainty analysis with this new meta-model based approach

An Analytical Model for Hysteretic Pressure-Sensitive Permeability of Nanoporous Media

Hysteretic pressure-sensitive permeability of nanohybrids composed of substantial nanopores is critical to characterizing fluid flow through nanoporous media. Due to the nanoscale effect (gas slippage), complex and heterogeneous pore structures of nanoporous media, the essential controls on permeability hysteresis of nanohybrids are not determined. In this study, a hysteretic pressure sensitive permeability model for nitrogen flow through dry nanoporous media is proposed. The derived model takes into account the nanoscale effect and pore deformation due to effective stress. The model is validated by comparing it with the experimental data. The results show that the calculated permeability and porosity are consistent with the measured results with the maximum relative error of 6.08% and 0.5%, respectively. Moreover, the hysteretic pressure-sensitive permeability of nanohybrids is related to effective stress, gas slippage, pore microstructure parameters, grain quadrilateral angle, and the loss rate of grain quadrilateral angle. The nanoscale effect is crucial to the permeability of nanoporous media. In addition, as impacted by the comprehensive impact of multiple relevant influential parameters, permeability during the pressure unloading process is not a monotonous function but presents complicated shapes. The proposed model can explain, quantify, and predict the permeability hysteresis effect of nanoporous media reasonably well